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Author:

Luo, C. (Luo, C..) | Peng, Y. (Peng, Y..)

Indexed by:

EI Scopus SCIE

Abstract:

Quantifying the near-fault effect and establishing a reasonable model of near-fault pulse-like ground motions are particularly important for seismic design of structures in near-fault regions. Given the pronounced randomness associated with earthquakes, this study first proposes a novel stochastic model of near-fault pulse-like ground motions by combining the improved finite-fault model (IFFM) and the multivariate copula-based velocity-pulse model (CVPM). Further, a probability density evolution method (PDEM) based stochastic simulation method is developed, by which the model parameters can be determined in a unified probability space so as to ensure the consistency of two independent models. For illustrative purposes, the observed records collected from the 1999 Chi-Chi earthquake are used to generate new stochastic ground motions set. Two ground motions sets based on classical stochastic simulation methods are also presented for comparison. Numerical results show that the proposed method for stochastic simulation of near-fault pulse-like ground motions is reliable; the statistics of peak ground accelerations and spectral characteristics of simulated samples are consistent with station records. Besides, the proposed method accommodates the noteworthy randomness and proportion consistency of components associated with near-fault pulse-like ground motions, making it suitable for the stochastic response and reliability analysis of seismic structures in near-fault regions. This superiority is challenging to classical stochastic simulation methods that lack reasonable consideration of randomness and correlation associated with model parameters. © 2024 Elsevier Ltd

Keyword:

Probability density evolution method Stochastic simulation Velocity-pulse model Finite-fault model Near-fault ground motions Multivariate copula

Author Community:

  • [ 1 ] [Luo C.]State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai, 200092, China
  • [ 2 ] [Luo C.]College of Civil Engineering, Tongji University, Shanghai, 200092, China
  • [ 3 ] [Peng Y.]State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai, 200092, China
  • [ 4 ] [Peng Y.]Shanghai Institute of Disaster Prevention and Relief, Tongji University, Shanghai, 200092, China
  • [ 5 ] [Peng Y.]The Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, Beijing, 100124, China

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Source :

Probabilistic Engineering Mechanics

ISSN: 0266-8920

Year: 2024

Volume: 76

2 . 6 0 0

JCR@2022

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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